DETECTION OF SOCCER GOAL SHOTS USING JOINT MULTIMEDIA FEATURES AND CLASSIFICATION RULES

ABSTRACT As digital video data becomes more and more pervasive, the issue of mining information from video data becomes increasingly important. In this paper, we present an effective data mining framework for automatic extraction of goal events in soccer videos. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The proposed multimedia data mining framework first analyzes the soccer videos by using joint multimedia features (visual and audio features). Then the data pre-filtering step is performed on raw video features with aid of domain knowledge, and the pre-filtered data are used as the input data in the data mining process using classification rules. The proposed framework fully exploits the rich semantic information contained in visual and audio features for soccer video data, and incorporates the data mining process for effective detection of soccer goal events. This framework has been tested using soccer videos with different styles as produced by different broadcasters. The results are promising and can provide a good basis for analyzing the high-level structure of video content.